Micromachined inertial measurement units (IMUs) have seen a steady improvement in their performance, with recent reports of microelectromechanical systems (MEMS) gyroscopes demonstrating bias stability of 0.1-1°/hr and angular random walk (ARW) of 0.01-0.1°/√hr. However, long-term drifts in scale-factor (gain) and bias still limit the potential of the inertial sensors in high accuracy strategic and navigation applications. To achieve higher performance and reliability of the inertial sensors there needs to be not just new inertial sensor designs, but also an integration of smart control functions for self-testing and self-calibration. In addition to self-compensation of bias drifts, it is highly desirable to integrate on-chip scale factor calibration mechanisms in order to improve the long-term output stability of inertial sensors against various factors such as aging, humidity, shock, external vibration, temperature variation, and temperature cycling.
Previously reported self-test and self-calibration methods for improvement of bias and gain stability in inertial sensors, includes on-chip calibration of scale factor against temperature variation by tracking the drive-mode resonance frequency for temperature sensing, thus reducing the scale factor error to 700 ppm in a small temperature range. Another self-calibration method is to use the gravitational force on the gyroscope proof mass as a reference for the Coriolis force, while a 1.2% deviation is measured between self-tested and actual scale factors. Another on-chip scale factor calibration method is to create a virtual rate input on the gyroscope as an input reference.
In another example, amplitude-modulated electrostatic excitation is applied to the drive and sense electrodes to mimic the Coriolis force resulting from an external rotation, while the phase-shift of the device output is measured. In such instances, to obtain the actual read-out scale factor, the measured calibration scale factor is readjusted by a ratio depending on the angular gain and the frequency split between resonance modes. The gain adjustment may introduce some inaccuracies, including a matching error between the estimated and rate-table measured scale factors of 3%.
In another example, additional electrostatic comb-drive electrodes are excited with a modulated signal constructed from virtual vibration velocity and virtual angular rate signals. After the gain adjustment of the measured frequency response, which is based on the gyroscope and driving parameters, the scale factor and bandwidth are determined within the 3% deviation of rate-table measurements. In some instances, a virtual input rate can be introduced to a closed-loop operated vibratory gyroscope by injecting a known square-wave modulated dither signal at a frequency out of the force-rebalance bandwidth. Such results in a deviation of the vibration pattern angle of the gyroscope from its nominal null position through the use of whole-angle mode. Thus, scale factor drifts are continuously observed and compensated with 350 ppm RMS accuracy between true and estimated values at 25° C. to 35° C.
As seen, in virtual-rate calibration methods, the use of emulated Coriolis forces require an additional gain adjustment in the output and is subject to possible deviation in excitation amplitude resulting from aging, which may limit the accuracy of measured scale factor in long-term field use. An alternative approach is to provide controlled on-chip physical stimuli for in situ measurement and recalibration of signal drift from an inertial sensor. This approach requires a compact and low-power micro-actuator that can produce the required reference calibration signals with minimum wobble or noise while not causing any degradation in gyroscope performance, as well as a precise motion sensing and estimation method.
In one example, integration of both an electromagnetic micro-actuator and an accelerometer on a same platform is disclosed. Specifically, where piezoresistive sensing and an over-range stopper are used to provide a reference impact. However, in such instances, self-calibration is not demonstrated and the measured actuation displacement is very small, approximately 2 nm.
In another example, co-fabrication of an SOI gyroscope on an electrostatic in-plane vibratory actuation platform is disclosed. In such instances, an open-loop high-frequency angular oscillation is used as a reference signal for calibration. Although self-measurement of frequency response of the detection oscillator is shown, the on-chip scale factor calibration or output comparison to rate-table characterization is not demonstrated.
In another example, preliminary results are collected for micro-scale rotary motors based on magnetoelastic, ultrasonic, and electrostatic actuation mechanisms. The goal in collecting such information is to calibrate a gyroscope mounted on the moving rotary stage by applying known continuous rotational rates (carouseling) or ±180° bidirectional dithering (maytagging). However, there are several challenges to overcome in applying such a method. The challenges include integration of reliable electrical connections between stator and rotor, active/passive shock protection mechanisms, and minimization of wobble and lateral slop during actuation.
This section provides background information related to the present disclosure which is not necessarily prior art.